{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "42145ff5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ['OMP_NUM_THREADS'] = '4'\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import openai\n",
    "openai.api_key = openai.api_key = \"XXXX\" #use your openai api key here\n",
    "from data.serialize import SerializerSettings\n",
    "from models.utils import grid_iter\n",
    "from models.llmtime import get_llmtime_predictions_data\n",
    "from data.small_context import get_datasets\n",
    "from models.validation_likelihood_tuning import get_autotuned_predictions_data\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "def plot_preds(train, test, pred_dict, model_name, show_samples=False):\n",
    "    pred = pred_dict['median']\n",
    "    pred = pd.Series(pred, index=test.index)\n",
    "    plt.figure(figsize=(8, 6), dpi=100)\n",
    "    plt.plot(train)\n",
    "    plt.plot(test, label='Truth', color='black')\n",
    "    plt.plot(pred, label=model_name, color='purple')\n",
    "    # shade 90% confidence interval\n",
    "    samples = pred_dict['samples']\n",
    "    lower = np.quantile(samples, 0.05, axis=0)\n",
    "    upper = np.quantile(samples, 0.95, axis=0)\n",
    "    plt.fill_between(pred.index, lower, upper, alpha=0.3, color='purple')\n",
    "    if show_samples:\n",
    "        samples = pred_dict['samples']\n",
    "        # convert df to numpy array\n",
    "        samples = samples.values if isinstance(samples, pd.DataFrame) else samples\n",
    "        for i in range(min(10, samples.shape[0])):\n",
    "            plt.plot(pred.index, samples[i], color='purple', alpha=0.3, linewidth=1)\n",
    "    plt.legend(loc='upper left')\n",
    "    if 'NLL/D' in pred_dict:\n",
    "        nll = pred_dict['NLL/D']\n",
    "        if nll is not None:\n",
    "            plt.text(0.03, 0.85, f'NLL/D: {nll:.2f}', transform=plt.gca().transAxes, bbox=dict(facecolor='white', alpha=0.5))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5d43ef37",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6b629ef4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_preds2(train, test, pred_dict, model_name, show_samples=False,plot_median=False):\n",
    "    pred_median = pred_dict['median']\n",
    "    pred_median = pd.Series(pred_median, index=test.index)\n",
    "    \n",
    "    \n",
    "    pred_mean = pred_dict['mean']\n",
    "    pred_mean = pd.Series(pred_mean, index=test.index)\n",
    "    \n",
    "    mse_median = mean_squared_error(test, pred_median)\n",
    "    mae_median =mean_absolute_error (test,pred_median)\n",
    "    mse_mean = mean_squared_error(test, pred_mean)\n",
    "    mae_mean = mean_absolute_error(test,pred_mean)\n",
    "    plt.figure(figsize=(8, 6), dpi=100)\n",
    "    plt.plot(train, label='Train', color='blue')\n",
    "    plt.plot(test, label='Truth', color='black')\n",
    "    if plot_median:\n",
    "        plt.plot(pred_median, label=f'Pred_Median (MSE: {mse_median:.2f}, MAE: {mae_median:.2f})', color='purple')\n",
    "    plt.plot(pred_mean, label=f'Pred_Mean (MSE: {mse_mean:.2f}, MAE: {mae_mean:.2f})', color='red')\n",
    "\n",
    "    samples = pred_dict['samples']\n",
    "    lower = np.quantile(samples, 0.05, axis=0)\n",
    "    upper = np.quantile(samples, 0.95, axis=0)\n",
    "    plt.fill_between(pred_median.index, lower, upper, alpha=0.3, color='purple')\n",
    "    \n",
    "    if show_samples:\n",
    "        samples = samples.values if isinstance(samples, pd.DataFrame) else samples\n",
    "        for i in range(min(10, samples.shape[0])):\n",
    "            plt.plot(pred_median.index, samples[i], color='purple', alpha=0.3, linewidth=1)\n",
    "    \n",
    "    plt.legend(loc='upper left')\n",
    "    \n",
    "    if 'NLL/D' in pred_dict:\n",
    "        nll = pred_dict['NLL/D']\n",
    "        if nll is not None:\n",
    "            plt.text(0.03, 0.85, f'NLL/D: {nll:.2f}', transform=plt.gca().transAxes, bbox=dict(facecolor='white', alpha=0.5))\n",
    "    \n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1341ded",
   "metadata": {},
   "source": [
    "## Define models ##"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1bdf1f3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "arima_hypers = dict(p=[12,30], d=[1,2], q=[0])\n",
    "\n",
    "gpt_hypers = dict(\n",
    "    temp=0.6,\n",
    "    alpha=0.95,\n",
    "    beta=0.7,\n",
    "    basic=True,\n",
    "    settings=SerializerSettings(base=10, prec=3, signed=True, half_bin_correction=True)\n",
    ")\n",
    "\n",
    "model_hypers = {\n",
    "    'LLMTime GPT-3.5': {'model': 'gpt-3.5-turbo-instruct', **gpt_hypers},\n",
    "    \n",
    "    \n",
    "}\n",
    "\n",
    "model_predict_fns = {\n",
    "    'LLMTime GPT-3.5': get_llmtime_predictions_data,\n",
    "   \n",
    "}\n",
    "\n",
    "model_names = list(model_predict_fns.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2da9a874",
   "metadata": {},
   "source": [
    "## Running LLMTime and Visualizing Results ##"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ac8ccc3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset: AirPassengersDataset\n",
      "(115,) (29,)\n"
     ]
    }
   ],
   "source": [
    "datasets = get_datasets()\n",
    "ds_name = \"AirPassengersDataset\"\n",
    "\n",
    "data = datasets[ds_name]\n",
    "train, test = data # or change to your own data\n",
    "out = {}\n",
    "print(f\"Dataset: {ds_name}\")\n",
    "print(train.shape, test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d394a097",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sampling with best hyper... defaultdict(<class 'dict'>, {'model': 'gpt-3.5-turbo-instruct', 'temp': 0.6, 'alpha': 0.95, 'beta': 0.7, 'basic': True, 'settings': SerializerSettings(base=10, prec=3, signed=True, fixed_length=False, max_val=10000000.0, time_sep=' ,', bit_sep=' ', plus_sign='', minus_sign=' -', half_bin_correction=True, decimal_point='', missing_str=' Nan'), 'dataset_name': 'AirPassengersDataset'}) \n",
      " with NLL inf\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/1 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now is LSTP prompting\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:08<00:00,  8.09s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train=train[:]\n",
    "all_time_steps=35\n",
    "breath_steps=12\n",
    "dataname=\"the monthly total number of AirPassengers\" \n",
    "num_samples=10\n",
    "prompt_method=\"LSTP\"#LSTP or LLM-TIME \n",
    "#The LSTPrompt defaults to using GPT-4 and is based on preprocessing of llmtime.\n",
    "\n",
    "for model in model_names: \n",
    "    model_hypers[model].update({'dataset_name': ds_name}) \n",
    "    hypers = list(grid_iter(model_hypers[model]))\n",
    "    num_samples = num_samples\n",
    "    pred_dict = get_autotuned_predictions_data(train[:], test, hypers, num_samples, model_predict_fns[model], verbose=False, parallel=False,prompt_method=prompt_method,all_time_steps=all_time_steps,breath_steps=breath_steps,dataname=dataname)\n",
    "    means = {}\n",
    "    samples = pred_dict['samples']\n",
    "    for col in samples.columns:\n",
    "        current_column = samples[col]\n",
    "        \n",
    "        std_dev = current_column.std()\n",
    "        mean = current_column.mean()\n",
    "        \n",
    "        lower_bound = mean - 1.5 * std_dev\n",
    "        upper_bound = mean + 1.5 * std_dev\n",
    "        \n",
    "        filtered_column = current_column[(current_column >= lower_bound) & (current_column <= upper_bound)]\n",
    "        \n",
    "        means[col] = filtered_column.mean()\n",
    "\n",
    "    means_series = pd.Series(means)\n",
    "    pred_dict['mean'] = means_series\n",
    "    out[model] = pred_dict\n",
    "    plot_preds2(train, test, pred_dict, model, show_samples=True,plot_median=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a2059d46",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sampling with best hyper... defaultdict(<class 'dict'>, {'model': 'gpt-3.5-turbo-instruct', 'temp': 0.6, 'alpha': 0.95, 'beta': 0.7, 'basic': True, 'settings': SerializerSettings(base=10, prec=3, signed=True, fixed_length=False, max_val=10000000.0, time_sep=' ,', bit_sep=' ', plus_sign='', minus_sign=' -', half_bin_correction=True, decimal_point='', missing_str=' Nan'), 'dataset_name': 'AirPassengersDataset'}) \n",
      " with NLL inf\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/1 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now is LLM-TIME prompting\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:04<00:00,  4.49s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train=train[:]\n",
    "\n",
    "num_samples=10\n",
    "prompt_method=\"LLM-TIME\"#LSTP or LLM-TIME \n",
    "\n",
    "for model in model_names:\n",
    "    model_hypers[model].update({'dataset_name': ds_name}) \n",
    "    hypers = list(grid_iter(model_hypers[model]))\n",
    "    num_samples = num_samples\n",
    "    pred_dict = get_autotuned_predictions_data(train[:], test, hypers, num_samples, model_predict_fns[model], verbose=False, parallel=False,prompt_method=prompt_method,all_time_steps=all_time_steps,breath_steps=breath_steps,dataname=dataname)\n",
    "    means = {}\n",
    "    samples = pred_dict['samples']\n",
    "    for col in samples.columns:    \n",
    "        current_column = samples[col]\n",
    "        means[col] = current_column.mean()\n",
    "\n",
    "    means_series = pd.Series(means)\n",
    "    pred_dict['mean'] = means_series\n",
    "    out[model] = pred_dict\n",
    "    plot_preds2(train, test, pred_dict, model, show_samples=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "52ee1a36",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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